Developers can improve LLM performance and reduce costs by correctly separating system prompts from user prompts. Stable instructions, rules, and persona details should reside in the system prompt for caching benefits, while dynamic data like user input, timestamps, or user-specific information belongs in the user message. Incorrectly mixing these elements, such as embedding a timestamp or user ID into the system prompt, invalidates the cache and forces the model to re-process the entire prompt on each call, leading to higher costs and reduced steerability. AI
IMPACT Proper prompt separation can significantly reduce API costs and improve LLM response reliability by enabling effective caching.
RANK_REASON The item provides advice and best practices for prompt engineering, rather than announcing a new product, research, or significant industry event.
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
